Data Management Plan

Wild rice (manoomin) plays an integral role in the ecosystems, culture, and economy of the Lake Superior region and it faces an existential threat from invasive species which compete for the same habitat and a variety of other factors. Six Areas of Interest (AOI) were identified as pilot sites and selected as the target AOI for this project.

AOI/Pilot Sites

1. Crooked Lake, Sucker Lake, and the Ontonagon River (CSO)

2. Eastern Upper Peninsula (EUP)*

3. Fond du Lac (FDL)

4. Kakagon Sloughs and Bad River (KSBR)

5. St. Louis River Estuary (SLRE)

6. Upper St. Louis River (USLR)

*To request imagery, please contact NOAA Office for Coastal Management (NOAA/OCM) at coastal.info@noaa.gov.

Process Steps:

• 2018-01-01 00:00:00 - The following section details the steps taken to pre-process the data. Processing Level 1a – Radiometric Correction 1. Dark Noise Removal Dark image data was acquired for every raw image at the end of every flight line by the sensor control software closing the shutter and recording 5 seconds of dark noise. To remove sensor noise the mean value of every line of the dark data was subtracted from the corresponding line of the raw data (dark noise removal or dark current removal). 2. Calibration from RAW data to radiance data using calibration file After the dark noise removal, the raw data was calibrated to radiance units using a sensor specific calibration file. Every spatial and spectral pixel is multiplied with the corresponding value in the calibration file. The calibration values for each pixel on the CCD are calculated using an integrating sphere in the laboratory. The radiance units are equal to (mW/cm^2*str*um)*1000.00. 3. Smile Correction Spectral smile is defined as changes in wavelength over the field of view (FOV). Smile correction was performed by proprietary algorithms. 4. Crosstrack Correction A crosstrack correction was performed using proprietary algorithm in order to normalize illumination in the across-track direction of each flight line. 5. Quality Control Quality control was accomplished using ASD measurements, established radiometric quality protocols and systematic manual evaluations. Applied Hyperspectral Imaging Services 25 25 Processing Level 1b – Atmospheric Correction 1. Atmospheric Correction The radiance units were converted to reflectance units using the ASD spectrometer measurements of uniform surfaces (parking lots, asphalt, sand and concrete) that were collected in the field. Multiple spectrometer measurements were taken at each site under clear conditions to ensure data quality. An “empirical line correction” method was used to calibrate every flight line to reflectance. After the correction an adaptive spectral filter was used to smooth the reflectance values and to eliminate outliers and spikes in the spectra. The reflectance units are equal to Reflectance*10000. 2. Quality Control Quality control was accomplished using ASD spectrometer measurements, established atmospheric correction quality protocols and systematic manual evaluations.
• 2018-01-01 00:00:00 - Processing Level 2 – Geometric Correction 1. Calculation of the sensor offset (Boresight correction) During the aerial acquisition, four special Boresight flight lines were flown to geometrically calibrate the sensor and GPS/INS. The Boresight parameters were calculated using four overlapping flight lines flown in a crosshair pattern. 15 to 20 Ground Control Points per flight line pair (GCPs) were identified and used to calculate geometric correction values for Roll (0.162353), Pitch (0.131388) and Yaw (0.166983). These values were then used as input parameters for the geometric correction process. 2. GPS/INS Data The GPS/INS Data was encoded and processed for the use in the georectification process 3. GLT files (Geographic Lookup Table) A GLT file contains the geographic location of every pixel in the unrectified reflectance data. A GLT file was generated for every flight line using the GPS/INS Data, the Boresight Correction parameters and a Digital Elevation Model (DEM) Processing Level 3 – Orthorectification Applied Hyperspectral Imaging Services 26 26 1. Georectification using GLT data The unrectified reflectance data was then Georectified into North American Datum of 1983 (NAD83) and projected into the Universal Transverse Mercator (UTM) coordinate system using the corresponding GLT file. A DEM was used to correct for surface elevation variation across the scene. 2. Mosaicking Individual flight lines for each AOI were combined into a single mosaic image which covered the entire AOI. This image was then masked to the AOI boundary and tiled according to the tiling scheme vectors included with this delivery. 3. Quality Control Geo-accuracy was checked and confirmed to meet pre-established quality standards by systematic comparison of specific geo-locations acquired in the field with a GPS unit and high resolution RGB imagery of known geo-accuracy.